Create and manage training data:
in one place, across teams, at scale

Labelbox is a collaborative annotation platform for artificial intelligence applications.

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Labelbox raises $3.9M from Kleiner Perkins, First Round and Google's new AI fund, Gradient Ventures. Read the TechCrunch article.


We partner with amazing businesses - big and small

How you interpret your data is everything

  • Images
  • Maps
  • Build your own

Classification and segmentation with powerful image annotation tools: bounding boxes, polygon, point, line, brush, and superpixel.

Imagery from drones and satellites are often processed to form a mosaic of an area using techniques like photogrammetry. Use Labelbox to create bounding boxes and polygons directly on the tiled imagery (zoomable maps). Ideal for drone maps, satellite imagery and even medical data.

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Start with a standard interface and customize infinitely to take on any type of project. Many of our users use Labelbox to annotate text, audio, point clouds and video.

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Measure and Improve

  • Workflows
  • Quality
  • Efficiency

Construct multi-step processes by combining manual annotation tasks, model-assisted labeling, and quality checks.                                                  

The quality of your data determines the quality of your product. Real-time, automatic visibility and control over your data pipeline, no matter how many teams or collaborators.

Keep your teams efficient with live metrics, wherever they are.

​Label data with your team, an external team, or both.

Whether you have an in-house team of experts or are using a managed workforce to label data, you can bring all of this in one place with flexible collaboration and management tools.

​Integrate with the best frameworks and formats

  • TensorFlow
  • Others

Interface directly into TensorFlow's native format (.TFrecords).

Export in other popular formats: JSON, CSV, Pascal VOC, and COCO.





Learning is continuous

Create models that keep up with the real world. Monitor, improve, and manage model predictions with Labelbox.


from graphqlclient import GraphQLClient
client = GraphQLClient('https://api.labelbox.com/graphql')
client.inject_token('LABELBOX_API_KEY_HERE')

data = client.execute('''
query {
	projects {
		name,
		labels(first:1) {
			id,
			label
		}
	}
}
''')

print(data)

​Extensible and Developer Friendly

Labelbox is an API first product. You can build and operate fully automated human in the loop machine learning pipelines.

Testimonials

"The team at Labelbox managed to create a powerful, easy-to-use and configurable system that fulfills the requirements that we identified in our research. We are using it in combination with our medical partners to create open, unique, and societally important datasets. It works perfectly! If you want to use the best tool out there, you should use Labelbox."

Michael Riegler, PhD

Senior Research Scientist, Simula Research Laboratory

"Incorporating Labelbox into our process was a huge step forward for our team."

Paul Fryzel

Principal Engineer, FORE, Condé Nast

"I really love the simplicity of a solution that still provides amazing functionality. The team is easy to get in touch with and are constantly working to improve Labelbox through user feedback and innovation. I highly recommend Labelbox for any size team that is working on a project that requires image segmentation or classification"

Zach Mostowsky

Engineer, NT Concepts

Join the community of businesses using Labelbox to
create the next industrial revolution.

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